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Bootstrapping Using Services from Helsinki: Juha Lehtonen, CEO of FA Solutions (Part 3)

Posted on Wednesday, Feb 23rd 2022

Sramana Mitra: All your early customers were in Finland?

Juha Lehtonen: Yes, the early customers were local. Once we were up and running, it took us about a year and a half to launch the product. We did it very gradually. Around 2008, we heard that there was a couple of Swedish guys in sales who were setting up their company in Sweden.

Their goal was to find two or three software products that they wanted to represent. We were able to get started with them. We were among those three software that they represented in Sweden. That was the beginning of a little bit of the international market.

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Bootstrapping a Vertical CRM Product using Services: Cleverping CEO Haysam Ali (Part 1)

Posted on Tuesday, Feb 22nd 2022

Haysam has built a $10M services business and alongside, he has bootstrapped a vertical CRM product for the telecom industry.

Read on to understand the nuances.

Sramana Mitra: Let’s start with the very beginning of your journey. Where are you from? Where were you born, raised, and in what kind of background?

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Bootstrapping Using Services from Helsinki: Juha Lehtonen, CEO of FA Solutions (Part 2)

Posted on Tuesday, Feb 22nd 2022

Sramana Mitra: What were the deal sizes?

Juha Lehtonen: It was very little – annual fees of €20,000. It was more like an advertisement for us. In addition to developing the platform, we did quite a lot of projects. We needed to self-finance. After the initial investment, we didn’t raise any other capital. That was the only capital we got. We ended up building up a consultation business.

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Bootstrapping Using Services from Helsinki: Juha Lehtonen, CEO of FA Solutions (Part 1)

Posted on Monday, Feb 21st 2022

European companies often follow a methodical, deliberate approach to business building as opposed to mindlessly chasing venture capital.

Juha has used the principles of bootstrapping using services to build his venture from Finland.

Sramana Mitra: Let’s start at the very beginning of your journey. Where are you from? Where were you born, raised and in what kind of background?

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From Developer to Successful Machine Learning Entrepreneur: Aparna Dhinakaran, Co-Founder, CPO of Arize (Part 7)

Posted on Sunday, Feb 20th 2022

Sramana Mitra: It’s true about men also. Unless you come from our kinds of backgrounds, you don’t reach this community. If you come from an average background, you don’t have much of a choice than go through the bootstrapping route. We belong to a very privileged elite class of people who have access. Most of the industries don’t have that access.

Aparna Dhinakaran: Maybe we agree to disagree on this one.

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From Developer to Successful Machine Learning Entrepreneur: Aparna Dhinakaran, Co-Founder, CPO of Arize (Part 6)

Posted on Saturday, Feb 19th 2022

Sramana Mitra: You believe there is a bias from customers?

Aparna Dhinakaran: No, I think there is a bias in the tech industry itself. In general, there are not that many women that go into AI. I don’t think that we can argue that we’ve reached a neutral point. If I saw that in reality, there would be more women founders.

Sramana Mitra: I’m not asking you the question on statistics. I’m asking about your personal experience. Do you face bias from customers?

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From Developer to Successful Machine Learning Entrepreneur: Aparna Dhinakaran, Co-Founder, CPO of Arize (Part 5)

Posted on Friday, Feb 18th 2022

Sramana Mitra: So what use cases did you find the maximum traction in?

Aparna Dhinakaran: AdTech click-through rate is a common use case. Fraud is a big one. Lending is a big one. Demand forecasting is another big one. There are these common use cases.

Sramana Mitra: Are you direct selling?

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From Developer to Successful Machine Learning Entrepreneur: Aparna Dhinakaran, Co-Founder, CPO of Arize (Part 4)

Posted on Thursday, Feb 17th 2022

Sramana Mitra: How did you generate inbound interest?

Aparna Dhinakaran: Cold emails. It works. I just told them that I’m building a company focused on ML observability. We spent months doing this. Every call we were on, we showed them our mocks. We asked them for feedback. At the end of these calls, people would say, “When is this going to be released?” We started to build up a list of alpha users.

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